Sensor Networks: ISSNIP Research Themes


Wireless sensor networks are potentially one of the most important technologies of this century. Consequently, billions of dollars are being committed to the research and development of sensor networks in order to address the many technical challenges and wide range of immediate applications.

Advances in hardware development have made available the prospect of low cost, low power, miniature devices for use in remote sensing applications. The combination of these factors has improved the viability of utilizing a sensor network consisting of a large number of intelligent sensors, enabling the collection, processing analysis and dissemination of valuable information gathered in a variety of environments.

A sensor network is an array (possibly very large) of sensors of diverse type interconnected by a communications network. Sensor data is shared between the sensors and used as input to a distributed estimation system which aims to extract as much relevant information from the available sensor data. The fundamental objectives for sensor networks are reliability, accuracy, flexibility, cost effectiveness and ease of deployment.

A sensor network is made up of individual multifunctional sensor nodes. The sensor node itself may be composed of various elements such as various multi-mode sensing hardware (acoustic, seismic, infrared, magnetic, chemical, imagers, microradars), embedded processor, memory, power-supply, communications device (wireless and/or wired) and location determination capabilities (through local or global techniques).

Sensor networks are predominantly data-centric rather than address-centric. That is, queries are directed to a region containing a cluster of sensors rather than specific sensor addresses. Given the similarity in the data obtained by sensors in a dense cluster, aggregation of the data is performed locally. That is, a summary or analysis of the local data is prepared by an aggregator node within the cluster, thus reducing the communication bandwidth requirements. Aggregation of data increases the level of accuracy and incorporates data redundancy to compensate node failures. A network hierarchy and clustering of sensor nodes allows for network scalability, robustness, efficient resource utilization and lower power consumption.

Dissemination of sensor data in an efficient manner requires the dedicated routing protocols to identify shortest paths. Redundancy must be accounted for to avoid congestion resulting from different nodes sending and receiving the same information. At the same time, redundancy must be exploited to ensure network reliability. Data dissemination may be either query driven or based on continuous updates.

A sensor network can be described by services, data and physical layer respectively. Recognizing the significance of sensor networks and the associated network protocol requirements, the IEEE has defined a standard for personal area networks, (the IEEE 802.15 standard), specifically for networks with a 5 to 10 m radius.

Implicit throughout the operation of a sensor network is a variety of information processing techniques for the manipulation and analysis of sensor data, extraction of significant features, along with the efficient storage and transmission of the important information.

Significance / Benefits

Sensing accuracy: The utilization of a larger number and variety of sensor nodes provides potential for greater accuracy in the information gathered as compared to that obtained from a single sensor. The ability to effectively increase sensing resolution without necessarily increasing network traffic will increase the reliability of the information for the end user application.

Area coverage: A distributed wireless network incorporating sparse network properties will enable the sensor network to span a greater geographical area without adverse impact on the overall network cost.

Fault tolerance: Device redundancy and consequently information redundancy can be utilized to ensure a level of fault tolerance in individual sensors.

Connectivity: Multiple sensor networks may be connected through sink nodes, along with existing wired networks (eg. Internet). The clustering of networks enables each individual network to focus on specific areas or events and share only relevant information with other networks enhancing the overall knowledge base through distributed sensing and information processing.

Minimal human interaction: The potential for self-organizing and self-maintaining networks along with highly adaptive network topology significantly reduce the need for further human interaction with a network other than the receipt of information.

Operability in harsh environments:
Robust sensor design, integrated with high levels of fault tolerance and network reliability enable the deployment of sensor networks in dangerous and hostile environments, allowing access to information previously unattainable from such close proximity.

Dynamic sensor scheduling: Dynamic reaction to network conditions and the optimization of network performance through sensor scheduling. This may be achieved by enabling the sensor nodes to modify communication requirements in response to network conditions and events detected by the network, so that essential information is given the highest priority.

Significance and Challenges

Changing network topology: the variability of network topologies due to node failures, introduction of additional nodes, variations in sensor location, changes to cluster allocations in response to network demands, requires the adaptability of underlying network structures and operations.

Advanced communication protocols: are required to support high level services and real-time operation, adapting rapidly to extreme changes in network conditions.

Resource optimization: Optimised sensor scheduling for distributed networks, through accurate determination of the required density of sensor nodes in order to minimize cost, power and network traffic loads, while ensuring network reliability and adequate sensor resolution for data accuracy.

Limitations: power, memory, processing power, life-time. These physical constraints may be minimized through further technological breakthroughs in materials and sensor hardware designs.

Failure prone: individual sensors are unreliable, particularly in harsh and unpredictable environments. Addressing sensor reliability can reduce the level of redundancy required for a network to operate with the same level of reliability.

Network congestion resulting from dense network deployment: The quantity of data gathered may exceed the requirements of the network and so evaluation of the data and transmission of only relevant and adequate information needs the be performed.

Self-organization ability to adapt to dynamic environments as well as ad hoc distribution and connectivity scenarios.

Self-operating and self-maintaining functionality in order to minimize further human interaction beyond network deployment.

Security is a critical factor in sensor networks, given some of the proposed applications. An effective compromise must be obtained, between the low bandwidth requirements of sensor network applications and security demands (which traditionally place considerable strain on resources)


Current sensor network applications include military sensing, air traffic control, video surveillance, traffic surveillance industrial and manufacturing automation, robotics, infrastructure monitoring and environment monitoring. Future applications and capabilities may include the following:

Low cost, scalable surveillance solutions using unmanned aerial vehicles as an integrated sensor network for defense.

Advanced surveillance networks incorporating automated anomaly detection and adaptive reasoning in conjunction with secure protocols for event reporting.

Early disaster monitoring of sensitive environments (in the event of bushfires or flooding for example), employing a large geographically distributed sparse sensor network, utilizing inbuilt communication capabilities to potentially save lives as well as minimize associated economic impacts.

Reconfigurable networks able to optimize performance and information collection and dissemination according to varying local conditions and sensor node failure or isolation.
Habitat monitoring of environmentally sensitive areas using wireless distributed sensor networks to collect valuable information such as species diversity, ecosystem structure, and environmental change to determine the impact of factors such as global climate change and over-development.

Irrigation control utilizing a network of intelligent sensors able to collect various information pertaining to local weather, water supply and soil conditions in such a way as too provide feedback for the efficient distribution of water for crop management, integrated with long and short term weather forecasts.

Infrastructure security through a network and variety of sensor types provided early warnings of potential problems threats and reducing false positive alarms through the fusion of information from multiple sensor types.

Industrial sensing for equipment monitoring and maintenance, as well as efficiency enhancements in process flow.

Network Requirement

  1. Large number of sensors
  2. Low power
  3. Efficient memory use (to reduce memory size requirements and power use)
  4. Data aggregation
  5. Self-organisation
  6. Collaborative processing
  7. Querying ability
  8. Scalability
  9. Fault tolerance

National Importance

The development of sensor network technology is of great national importance by virtue of critical applications directly related to the Australian environment. Sensor networks provide the ability to gather accurate and reliable information, enabling early warnings and rapid coordinated responses to potential threats. This encompasses the ability to enhance national security from hostile threats as well as the ability to save lives through environmental monitoring of natural disasters. Environmental sustainability can also be improved through sensor network monitoring, by protecting valuable resources from overuse or damage, as well as being able to collect valuable information previously considered too difficult and too costly.


Satellite sensor communications

Sensor networks

Intelligent sensors

Sensor networks


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